Triple
T11313477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autoroute A9 |
E267901
|
entity |
| Predicate | terminusNear |
P1866
|
FINISHED |
| Object |
Orange
Orange is a historic town in southeastern France, renowned for its well-preserved Roman theatre and triumphal arch.
|
E3952
|
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: Orange | Statement: [Autoroute A9, terminusNear, Orange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Context triple: [Autoroute A9, terminusNear, Orange]
-
A.
Orange
Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
-
B.
Orange
Orange is the nickname and primary identity of Syracuse University's athletic teams, especially its prominent men's basketball program.
-
C.
Orange
Orange was the original name of the town now known as Hillsborough in North Carolina, reflecting its early colonial-era identity.
-
D.
Orange
Orange is a small town in north-central Massachusetts known for its rural character, historic mill village roots, and location along the Millers River.
-
E.
Orange
Orange is a common English surname of likely Norman or French origin, shared by various individuals including the British singer Jason Orange.
- 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: Orange Triple: [Autoroute A9, terminusNear, Orange]
Generated description
Orange is a historic town in southeastern France, renowned for its well-preserved Roman theatre and triumphal arch.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orange Target entity description: Orange is a historic town in southeastern France, renowned for its well-preserved Roman theatre and triumphal arch.
-
A.
Orange
chosen
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
B.
Orange
Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
-
C.
Orange
Orange is a small town in north-central Massachusetts known for its rural character, historic mill village roots, and location along the Millers River.
-
D.
Orange
Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
-
E.
Orange
Orange was the original name of the town now known as Hillsborough in North Carolina, reflecting its early colonial-era identity.
- F. None of above.
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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c1b7dc81908d8cc768c47390d3 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a910a2c8190b8afd4c988e64141 |
completed | April 19, 2026, 5:02 p.m. |
| NEDg | Description generation | batch_69e5167083fc8190b5cdbfca5b25b295 |
completed | April 19, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e51795f024819086bfe7deba485fdd |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 8, 2026, 9:32 p.m.