Triple
T6667995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterContinental Hotels Group |
E151652
|
entity |
| Predicate | numberOfCountriesOperatedIn |
P3809
|
FINISHED |
| Object | 100+ |
—
|
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: 100+ | Statement: [InterContinental Hotels Group, numberOfCountriesOperatedIn, 100+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesOperatedIn Context triple: [InterContinental Hotels Group, numberOfCountriesOperatedIn, 100+]
-
A.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
B.
hasNumberOfCountries
chosen
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
C.
operatedAmong
Indicates that an entity carried out operations or activities within, or in coordination with, a specified group, set, or collection of other entities.
-
D.
operatedInRegion
Indicates that an entity conducted operations or activities within a specified geographic region.
-
E.
operatesToContinents
Indicates that an entity conducts or provides operations or services that extend across or are directed toward multiple continents.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:02 p.m.