Triple
T13307129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El-Alaki |
E316963
|
entity |
| Predicate | locatedInGovernorateCapitalRegion |
P109434
|
FINISHED |
| Object | Aswan metropolitan area vicinity |
—
|
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: Aswan metropolitan area vicinity | Statement: [El-Alaki, locatedInGovernorateCapitalRegion, Aswan metropolitan area vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInGovernorateCapitalRegion Context triple: [El-Alaki, locatedInGovernorateCapitalRegion, Aswan metropolitan area vicinity]
-
A.
locatedInCapital
Indicates that an entity is situated within the capital city of a specified region, country, or administrative area.
-
B.
locatedInNationCapitalRegion
Indicates that an entity is situated within the capital region of a specific nation.
-
C.
locatedInCountryCapitalOfProvince
Indicates that an entity is located in the country that contains the capital city of a specified province.
-
D.
governorSeatRegion
Indicates the region in which a governor’s official seat or office is located.
-
E.
locatedInCapitalCityPort
Indicates that something is situated within the port area of a country's capital 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:29 p.m.