Triple
T28100035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Congrès de Tours de 1920 |
E710204
|
entity |
| Predicate | seTientDans |
P109650
|
FINISHED |
| Object | salle du Manège à Tours |
—
|
NE NERFINISHED |
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: salle du Manège à Tours | Statement: [Congrès de Tours de 1920, seTientDans, salle du Manège à Tours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seTientDans Context triple: [Congrès de Tours de 1920, seTientDans, salle du Manège à Tours]
-
A.
appartientÀ
Indicates that one entity belongs to, is a member of, or is part of another entity.
-
B.
locatedInTheInteriorOf
chosen
Indicates that one entity is situated entirely within the inner part or inside area of another entity, rather than on its surface or boundary.
-
C.
hasPartIn
Indicates that an entity participates in or plays a role within a larger event, process, or composite entity.
-
D.
sometimesLocatedIn
Indicates that an entity is located in a given place only at certain times or under certain conditions, rather than permanently or always.
-
E.
situéeDansLeDépartement
Indicates that one entity is located within the administrative boundaries of a specific department.
- F. None of above.
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_69ef9b70fd108190a875953b2e50ca91 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f640908b208190857b085879e60e1c |
completed | May 2, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 9:04 p.m.