Triple
T11224964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazara Motorway |
E265670
|
entity |
| Predicate | terminusNear |
P1866
|
FINISHED |
| Object | Hasan Abdal |
E409906
|
NE 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: Hasan Abdal | Statement: [Hazara Motorway, terminusNear, Hasan Abdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasan Abdal Context triple: [Hazara Motorway, terminusNear, Hasan Abdal]
-
A.
Hasan Abdal
chosen
Hasan Abdal is a historic town in northern Punjab, Pakistan, known as a key gateway to the northern areas and an important religious and transit hub.
-
B.
Hassan Kadam
Hassan Kadam is a gifted young Indian chef whose culinary talent and personal journey drive the narrative of the film "The Hundred-Foot Journey."
-
C.
Mohammad Nasih
Mohammad Nasih is an Indonesian academic who serves as the rector of Airlangga University, one of the country’s leading public universities.
-
D.
Nasir
Nasir is a creative work associated with Wyoming Sessions, likely a music release or recording project.
-
E.
Anas al-Abdah
Anas al-Abdah is a Syrian opposition politician who has held senior leadership roles in exile-based bodies opposing Bashar al-Assad’s government during the Syrian Civil War.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ee15d4819087449058addef597 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cc3ced708190adf7276865cfa715 |
completed | April 19, 2026, 12:36 p.m. |
Created at: April 8, 2026, 9:30 p.m.