Triple
T4301228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hautes-Pyrénées |
E99839
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Gers |
E64830
|
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: Gers | Statement: [Hautes-Pyrénées, borders, Gers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gers Context triple: [Hautes-Pyrénées, borders, Gers]
-
A.
Gers
chosen
Gers is a river in southwestern France that flows through the historical region of Gascony before joining the Garonne.
-
B.
The Gers
The Gers is a popular nickname for Rangers F.C., one of Scotland’s most successful and widely supported football clubs.
-
C.
Gersprenz
Gersprenz is a river in the German state of Hesse that flows through the Odenwald region before joining the Main River system.
-
D.
Gsell
Gsell is a surname of Germanic origin borne by various notable individuals, including artists, scholars, and public figures.
-
E.
Geva
Geva is a surname most notably associated with Tamara Geva, a Russian-American actress, dancer, and choreographer.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509fb2b88190a13ab88a5b924052 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c74d59688190820cef42c4228a3a |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:08 p.m.