Triple
T3903387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pink City |
E90547
|
entity |
| Predicate | appliedTo |
P1129
|
FINISHED |
| Object | city of Toulouse |
E16066
|
NE FINISHED |
How this triple was built (2 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: city of Toulouse | Statement: [Pink City, appliedTo, city of Toulouse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Toulouse Context triple: [Pink City, appliedTo, city of Toulouse]
-
A.
Toulouse
chosen
Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
-
B.
Montpellier
Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
-
C.
Montpellier, France
Montpellier, France is a historic and vibrant city in southern France near the Mediterranean coast, known for its medieval architecture, large student population, and role as a regional cultural and economic center.
-
D.
Toulon
Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
-
E.
Clermont-Ferrand
Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecf5a7188190a1c722ec83e3c6cd |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b528540ad48190ac86774c76a2ffd4 |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:21 p.m.