Triple
T33133269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganges |
E847930
|
entity |
| Predicate | distanceFromMontpellier |
P74869
|
FINISHED |
| Object | about 40 km north |
—
|
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 40 km north | Statement: [Ganges, distanceFromMontpellier, about 40 km north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMontpellier Context triple: [Ganges, distanceFromMontpellier, about 40 km north]
-
A.
distanceToMontpellierKm
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Montpellier.
-
B.
distanceToMarseilleKilometers
Indicates the physical distance, measured in kilometers, between a given location or entity and the city of Marseille.
-
C.
distanceFromToulouse
Indicates the measured spatial distance between a given entity and the location of Toulouse.
-
D.
distanceToPerpignan
Indicates the physical distance between a given place or entity and the city of Perpignan.
-
E.
distanceToToulouse
Indicates the spatial distance between a given entity’s location and the city of Toulouse.
- 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_69f3495961d88190b16ea542c2c5f825 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:27 a.m.