Triple
T15184733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle-Lion Films |
E362837
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object |
Eagle-Lion
Eagle-Lion is the commonly used name for Eagle-Lion Films, an American film production and distribution company active in the mid-20th century.
|
E1141271
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Eagle-Lion | Statement: [Eagle-Lion Films, knownAs, Eagle-Lion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eagle-Lion Context triple: [Eagle-Lion Films, knownAs, Eagle-Lion]
-
A.
Lion-Mher
Lion-Mher is a heroic figure from the Armenian epic cycle "Daredevils of Sassoun," renowned for his extraordinary strength and lion-like bravery.
-
B.
Roaring Lion
Roaring Lion is the costumed lion mascot that represents Finlandia University at its athletic events and school functions.
-
C.
Ligerz
Ligerz is a small Swiss municipality on the shores of Lake Biel in the canton of Bern, known for its vineyards and scenic lakeside setting.
-
D.
Lioni
Lioni is a small town and comune in the Campania region of southern Italy, known for its location in the Apennine hills and its reconstruction after the 1980 Irpinia earthquake.
-
E.
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eagle-Lion Triple: [Eagle-Lion Films, knownAs, Eagle-Lion]
Generated description
Eagle-Lion is the commonly used name for Eagle-Lion Films, an American film production and distribution company active in the mid-20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eagle-Lion Target entity description: Eagle-Lion is the commonly used name for Eagle-Lion Films, an American film production and distribution company active in the mid-20th century.
-
A.
Lion-Mher
Lion-Mher is a heroic figure from the Armenian epic cycle "Daredevils of Sassoun," renowned for his extraordinary strength and lion-like bravery.
-
B.
Roaring Lion
Roaring Lion is the costumed lion mascot that represents Finlandia University at its athletic events and school functions.
-
C.
Ligerz
Ligerz is a small Swiss municipality on the shores of Lake Biel in the canton of Bern, known for its vineyards and scenic lakeside setting.
-
D.
Lioni
Lioni is a small town and comune in the Campania region of southern Italy, known for its location in the Apennine hills and its reconstruction after the 1980 Irpinia earthquake.
-
E.
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006674c088190ba635a78c30f5637 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec893f1e08190a192b7b9b80484e8 |
completed | May 9, 2026, 5:39 a.m. |
| NEDg | Description generation | batch_69fec91a2d708190bcc67793c46b2a61 |
completed | May 9, 2026, 5:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feca0d38088190910dbf4f2538a9d4 |
completed | May 9, 2026, 5:45 a.m. |
Created at: April 10, 2026, 3:09 a.m.