Triple
T2397384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shepherds’ Field |
E47681
|
entity |
| Predicate | distanceFromBethlehem |
P37919
|
FINISHED |
| Object | a few kilometers |
—
|
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: a few kilometers | Statement: [Shepherds’ Field, distanceFromBethlehem, a few kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBethlehem Context triple: [Shepherds’ Field, distanceFromBethlehem, a few kilometers]
-
A.
distanceFromJerusalem
Indicates the spatial distance between a given location and Jerusalem.
-
B.
distanceFromJericho
Indicates the spatial distance separating an entity from the location of Jericho.
-
C.
distanceFromArafat
Indicates the spatial distance between a given entity and the location associated with Arafat.
-
D.
distanceFromBeirut
Indicates the measured spatial distance between a given entity’s location and the city of Beirut.
-
E.
distanceFromBaghdad
Indicates the spatial distance between a given location or entity and the city of Baghdad.
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc8c5f0948190b4ea729693d8c306 |
completed | March 7, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69abc5a3825c81909ec6111dfc165453 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc664317c8190a6bb5a5065c21bde |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:57 p.m.