Triple
T7489762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Cambrai (1595) |
E176975
|
entity |
| Predicate | hasLocation |
P40
|
FINISHED |
| Object | Cambrai, France |
E110945
|
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: Cambrai, France | Statement: [Siege of Cambrai (1595), hasLocation, Cambrai, France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cambrai, France Context triple: [Siege of Cambrai (1595), hasLocation, Cambrai, France]
-
A.
Cambrai
chosen
Cambrai is a historic city in northern France known for its medieval heritage, role in World War I, and traditional confectionery.
-
B.
Douai, France
Douai, France is a historic town in northern France known for its medieval belfry, legal and university traditions, and role as a regional administrative center.
-
C.
Saint-Omer
Saint-Omer is a historic town in northern France known for its medieval architecture, strategic military importance, and role in Franco-Spanish conflicts.
-
D.
Villeblevin, France
Villeblevin, France is a small commune in north-central France best known as the place where Nobel Prize–winning writer Albert Camus died in a car accident.
-
E.
Auxerre, France
Auxerre, France is a historic city in the Burgundy region known for its medieval architecture, Gothic cathedral, and role as a cultural and economic center along the Yonne River.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f55abcd481909e42ca857fe46cd1 |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84eefbcec8190bef282452aaf5515 |
completed | March 28, 2026, 9:58 p.m. |
Created at: March 27, 2026, 3:43 p.m.