Triple
T2489313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben-Gurion Airport |
E52001
|
entity |
| Predicate | distanceFromTelAviv_km |
P40351
|
FINISHED |
| Object | about 19 |
—
|
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 19 | Statement: [Ben-Gurion Airport, distanceFromTelAviv_km, about 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTelAviv_km Context triple: [Ben-Gurion Airport, distanceFromTelAviv_km, about 19]
-
A.
distanceFromJerusalem
Indicates the spatial distance between a given location and Jerusalem.
-
B.
distanceFromBeirut
Indicates the measured spatial distance between a given entity’s location and the city of Beirut.
-
C.
distanceFromJericho
Indicates the spatial distance separating an entity from the location of Jericho.
-
D.
distanceFromBethlehem
Indicates the spatial distance between a given location and Bethlehem.
-
E.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.