Triple
T17800970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muzaffargarh |
E444422
|
entity |
| Predicate | distanceToMultan |
P128976
|
FINISHED |
| Object | about 35–40 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 35–40 km | Statement: [Muzaffargarh, distanceToMultan, about 35–40 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMultan Context triple: [Muzaffargarh, distanceToMultan, about 35–40 km]
-
A.
distanceToLahore_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Lahore.
-
B.
distanceFromIslamabad
Indicates the spatial distance between a given location and the city of Islamabad.
-
C.
distanceFromKarachi
Indicates the measured spatial distance between a given entity’s location and the city of Karachi.
-
D.
distanceFrom Peshawar
Indicates the spatial distance between a given location or entity and the city of Peshawar.
-
E.
distanceFromRawalpindiCityCenter
Indicates the measured distance between a given location and the central point of Rawalpindi city.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487ff42108190b82ceb4466aa2dff |
completed | April 19, 2026, 7:45 a.m. |
| PD | Predicate disambiguation | batch_69e3d8de28688190844b65acf6af54e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:13 a.m.