Triple
T3840239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterloo |
E93431
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Rambouillet |
E132848
|
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: Rambouillet | Statement: [Waterloo, hasTwinTown, Rambouillet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rambouillet Context triple: [Waterloo, hasTwinTown, Rambouillet]
-
A.
Rambouillet, France
chosen
Rambouillet, France is a historic town southwest of Paris known for its royal château, former role as a French royal and presidential residence, and surrounding forest.
-
B.
Thoiry
Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
C.
Savoye
Savoye is a French surname most notably associated with the family who commissioned Le Corbusier’s iconic modernist Villa Savoye.
-
D.
Compiegne
Compiègne is a historic city in northern France known for its royal château, forest, and role in significant events such as the signing of the 1918 Armistice.
-
E.
Rocquencourt
Rocquencourt is a commune in north-central France that historically hosted key NATO military command facilities.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeba1535c8190b36e2ab2d4514b54 |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51228a7a48190bc42898be15b450b |
completed | March 14, 2026, 7:45 a.m. |
Created at: March 9, 2026, 3:18 p.m.