Triple
T3461892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umm Al Quwain |
E73042
|
entity |
| Predicate | numberOfEmiratesInCountry |
P16567
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Umm Al Quwain, numberOfEmiratesInCountry, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEmiratesInCountry Context triple: [Umm Al Quwain, numberOfEmiratesInCountry, 7]
-
A.
numberOfEmirates
chosen
Indicates the quantitative count of emirates associated with or contained within a given entity.
-
B.
emirate
Indicates that one entity is an emirate, i.e., a political territory or state ruled by an emir, in relation to another referenced entity.
-
C.
numberOfMemberAirlines
Indicates the total count of airlines that are members of a specified airline alliance or organization.
-
D.
hasNumberOfGovernorates
Indicates the total count of governorates associated with or contained within a given entity.
-
E.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
- F. None of above.
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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae867c4819091c76e63e44290b4 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.