Triple
T14949877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muhammad of Ghor |
E372761
|
entity |
| Predicate | territory |
P2160
|
FINISHED |
| Object | Ghor |
E139113
|
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: Ghor | Statement: [Muhammad of Ghor, territory, Ghor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ghor Context triple: [Muhammad of Ghor, territory, Ghor]
-
A.
Ghor
Ghor is a low-lying, fertile region within the Jordan Rift Valley known for its agricultural lands and proximity to the Jordan River.
-
B.
Ghor Province
chosen
Ghor Province is a mountainous, centrally located region of Afghanistan known for its remote terrain, historical significance, and ethnically diverse population.
-
C.
Ghorband
Ghorband is a notable town in Afghanistan’s Parwan Province, known for its location in a fertile valley northwest of Kabul.
-
D.
Khar
Khar is a town in northwestern Pakistan that serves as the administrative and commercial center of the Bajaur region in Khyber Pakhtunkhwa.
-
E.
Khar
Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68fae3c81909873b113bfcaca05 |
completed | April 15, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bd871188190afcba3be94dbfa94 |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:39 a.m.