Triple
T33986103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulle |
E871412
|
entity |
| Predicate | distanceToLimoges |
P205271
|
FINISHED |
| Object | about 90 km |
—
|
LITERAL 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: about 90 km | Statement: [Tulle, distanceToLimoges, about 90 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLimoges Context triple: [Tulle, distanceToLimoges, about 90 km]
-
A.
distanceToSaint-Étienne
Indicates the measured or specified distance between a given entity and the location Saint-Étienne.
-
B.
distanceToClermontFerrand_km
Indicates the physical distance, measured in kilometers, between a given place and Clermont-Ferrand.
-
C.
distanceToLePuy-en-Velay
Indicates the spatial distance between a given entity and the location of Le Puy-en-Velay.
-
D.
distanceFromAngersKilometres
Indicates the physical distance, measured in kilometers, between an entity and the location of Angers.
-
E.
distanceFromLyon
Indicates the spatial distance between a given entity and the city of Lyon.
- F. None of above. chosen
Provenance (4 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:50 a.m.