Triple
T12149585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emirs |
E289417
|
entity |
| Predicate | hasFemaleEquivalent |
P1613
|
FINISHED |
| Object | Emira |
E529779
|
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: Emira | Statement: [Emirs, hasFemaleEquivalent, Emira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emira Context triple: [Emirs, hasFemaleEquivalent, Emira]
-
A.
Emira
chosen
Emira is an alternate name for the Mussau-Emira language, an Oceanic language spoken in Papua New Guinea.
-
B.
Sitra
Sitra is a small island in Bahrain known for its residential communities, industrial facilities, and role in the country’s oil and gas infrastructure.
-
C.
Citura
Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
-
D.
Sauda
Sauda is a small industrial town and municipality in Rogaland county, Norway, known for its hydropower-based industry and dramatic fjord and mountain landscape.
-
E.
Qods
Qods is a city in Tehran Province, Iran, known primarily as the administrative center of Qods County within the Tehran metropolitan area.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915ad6ef08190b334a97d6ab41487 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f698c5648190a5a29e08f2b7d8ab |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.