Triple
T2734094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orléans |
E60387
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object |
Lugoj
Lugoj is a town in western Romania, situated on the Timiș River, known for its historical architecture and cultural heritage in the Banat region.
|
E291973
|
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: Lugoj | Statement: [Orléans, twinnedWith, Lugoj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugoj Context triple: [Orléans, twinnedWith, Lugoj]
-
A.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
B.
Albanopolis
Albanopolis is a historically obscure city or town, traditionally identified in Christian tradition as the place where the Apostle Bartholomew was martyred.
-
C.
Koksijde
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
-
D.
Evinayong
Evinayong is a town in mainland Equatorial Guinea that serves as an important local administrative and commercial center.
-
E.
Medgidia
Medgidia is a city in southeastern Romania, situated in the historical region of Dobruja and known as an important local industrial and transportation hub.
- 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: Lugoj Triple: [Orléans, twinnedWith, Lugoj]
Generated description
Lugoj is a town in western Romania, situated on the Timiș River, known for its historical architecture and cultural heritage in the Banat region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lugoj Target entity description: Lugoj is a town in western Romania, situated on the Timiș River, known for its historical architecture and cultural heritage in the Banat region.
-
A.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
B.
Albanopolis
Albanopolis is a historically obscure city or town, traditionally identified in Christian tradition as the place where the Apostle Bartholomew was martyred.
-
C.
Koksijde
Koksijde is a coastal municipality in West Flanders, Belgium, known for its North Sea beaches and seaside tourism.
-
D.
Evinayong
Evinayong is a town in mainland Equatorial Guinea that serves as an important local administrative and commercial center.
-
E.
Medgidia
Medgidia is a city in southeastern Romania, situated in the historical region of Dobruja and known as an important local industrial and transportation hub.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb6a15e548190a118880f9904f9cc |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb78d9f0c8190ad276922aa19945d |
completed | March 10, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb7e8a8548190b5b4e7772e0adcf6 |
completed | March 10, 2026, 6:19 a.m. |
Created at: March 6, 2026, 9:56 p.m.