Triple
T13340257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont du Gard |
E317805
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object | Gardon |
E317805
|
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: Gardon | Statement: [Pont du Gard, crosses, Gardon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gardon Context triple: [Pont du Gard, crosses, Gardon]
-
A.
Gardon
chosen
The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
-
B.
Gardo
Gardo is one of the three impoverished boys who uncover a dangerous secret while scavenging through a landfill in Andy Mulligan’s novel "Trash."
-
C.
Gavisse
Gavisse is a small commune in northeastern France, located in the Moselle department near the border with Luxembourg and Germany.
-
D.
Gardi
Gardi is the nickname of Ibrahim Khan Gardi, an 18th-century Indian military commander renowned for leading artillery forces in the Third Battle of Panipat.
-
E.
Gardish
Gardish is a 1993 Hindi action-drama film directed by Priyadarshan, known for Dimple Kapadia’s acclaimed performance alongside Jackie Shroff.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d01bf8481908cd3a99e5557b972 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f3ecf4c8190bb9eee699859dc08 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:31 p.m.