Triple
T13791065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Issoudun campus |
E331395
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Issoudun |
E241346
|
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: Issoudun | Statement: [Issoudun campus, locatedIn, Issoudun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Issoudun Context triple: [Issoudun campus, locatedIn, Issoudun]
-
A.
Issoudun
chosen
Issoudun is a historic commune in central France known for its medieval architecture and location within the Indre department.
-
B.
Boucha
Boucha is the surname of Henry Boucha, a notable American ice hockey player of Ojibwe heritage.
-
C.
Hillah
Hillah is a city in central Iraq on the Euphrates River, known as the modern settlement adjacent to the ruins of ancient Babylon.
-
D.
Medeba
Medeba is an ancient city east of the Dead Sea, known from biblical accounts and later as a significant settlement in the region of Moab.
-
E.
Yasmine City
Yasmine City is a modern seaside resort area in Hammamet, Tunisia, known for its hotels, marina, beaches, and tourist attractions.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de024af32c8190a9bd1278e09564ba |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0817bd88190a46e539f2ff24d83 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:11 p.m.