Triple
T15357599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Octan Corporation |
E367202
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Octan
Octan is a fictional, multinational energy and consumer goods conglomerate that appears as a major brand and corporation in the LEGO universe.
|
E1153458
|
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: Octan | Statement: [Octan Corporation, alsoKnownAs, Octan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Octan Context triple: [Octan Corporation, alsoKnownAs, Octan]
-
A.
Oktaha
Oktaha is a small town in eastern Oklahoma, United States, known as a rural community within the Muskogee metropolitan area.
-
B.
Octon
Octon is a small rural commune in southern France’s Hérault department, known for its proximity to the scenic Lac du Salagou and surrounding volcanic landscapes.
-
C.
Vintar
Vintar is a landlocked agricultural municipality in the province of Ilocos Norte in the Philippines, known for its rural landscapes and river valleys.
-
D.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
-
E.
Musina
Musina is a northern South African town in Limpopo Province, known as a key border and transport hub near Zimbabwe and for its history of copper and iron ore mining.
- 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: Octan Triple: [Octan Corporation, alsoKnownAs, Octan]
Generated description
Octan is a fictional, multinational energy and consumer goods conglomerate that appears as a major brand and corporation in the LEGO universe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Octan Target entity description: Octan is a fictional, multinational energy and consumer goods conglomerate that appears as a major brand and corporation in the LEGO universe.
-
A.
Oktaha
Oktaha is a small town in eastern Oklahoma, United States, known as a rural community within the Muskogee metropolitan area.
-
B.
Octon
Octon is a small rural commune in southern France’s Hérault department, known for its proximity to the scenic Lac du Salagou and surrounding volcanic landscapes.
-
C.
Vintar
Vintar is a landlocked agricultural municipality in the province of Ilocos Norte in the Philippines, known for its rural landscapes and river valleys.
-
D.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
-
E.
Musina
Musina is a northern South African town in Limpopo Province, known as a key border and transport hub near Zimbabwe and for its history of copper and iron ore mining.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2d4934819097fc63603964217c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b45e3048190a7fa62ead6916fed |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0f400ec08190961c63f957efe107 |
completed | May 9, 2026, 10:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0fbef36081908a0f6317a32f9c28 |
completed | May 9, 2026, 10:43 a.m. |
Created at: April 10, 2026, 3:18 a.m.