Triple
T31282229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masjid al-Tan‘im |
E797701
|
entity |
| Predicate | distanceFromMasjidAlHaram |
P203637
|
FINISHED |
| Object | approximately 6 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: approximately 6 kilometers | Statement: [Masjid al-Tan‘im, distanceFromMasjidAlHaram, approximately 6 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMasjidAlHaram Context triple: [Masjid al-Tan‘im, distanceFromMasjidAlHaram, approximately 6 kilometers]
-
A.
distanceFromKaaba
Indicates the spatial distance between an entity’s location and the Kaaba.
-
B.
distanceFromMecca
Indicates the measured spatial distance between a given location and the city of Mecca.
-
C.
distanceFromMeccaApprox
Indicates an approximate measure of how far something is located from Mecca.
-
D.
distanceFromJeddah
Indicates the measured spatial distance between a given entity and the location of Jeddah.
-
E.
distanceFromRiyadh
Indicates the measured spatial distance between a given entity’s location and the city of Riyadh.
- 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01bb06422c819095bb42f6f3a0e801 |
completed | May 11, 2026, 11:18 a.m. |
| PD | Predicate disambiguation | batch_6a01b9991c348190ac49b65ea2fd86ed |
completed | May 11, 2026, 11:12 a.m. |
| PDg | Predicate description generation | batch_6a01bb0584608190a27ad07f095ea7fd |
completed | May 11, 2026, 11:18 a.m. |
Created at: April 29, 2026, 9:13 p.m.