Triple
T17238906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haine |
E418435
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Mons |
E113627
|
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: Mons | Statement: [Haine, flowsThrough, Mons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mons Context triple: [Haine, flowsThrough, Mons]
-
A.
Mons
chosen
Mons is a Belgian town historically significant as the site of a major World War I battle in 1914, where British forces, including the Coldstream Guards, first engaged the German army on the Western Front.
-
B.
Montet
Montet is a French surname most notably borne by archaeologist Pierre Montet, renowned for his discoveries in the royal necropolis of Tanis in Egypt.
-
C.
La Mongie
La Mongie is a French Pyrenean ski resort village known as a gateway to the Pic du Midi de Bigorre and its observatory.
-
D.
Montjoi
Montjoi is a small commune in the Tarn-et-Garonne department in southern France, known for its rural setting within the Occitanie region.
-
E.
Eyraud
Eyraud is a French surname most notably borne by Eugène Eyraud, a 19th-century missionary known for his work on Easter Island.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dfdc8688190aceb223c19a48781 |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01676596a48190ae17a411b86e613e |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:39 a.m.