Triple
T35449893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legislature of American Samoa |
E1024596
|
entity |
| Predicate | hasNumberOfMembersInLowerHouse |
P51739
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Legislature of American Samoa, hasNumberOfMembersInLowerHouse, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMembersInLowerHouse Context triple: [Legislature of American Samoa, hasNumberOfMembersInLowerHouse, 21]
-
A.
hasLowerHouseSeats
chosen
Indicates the number of seats an entity holds in the lower house of a bicameral legislature.
-
B.
hasSpeakerInLowerHouse
Indicates that an entity serves as the presiding officer (speaker) of a specified lower house in a bicameral legislature.
-
C.
numberOfMembersUpperHouse
Indicates the total count of individuals serving as members in the upper house of a legislative body.
-
D.
hasLowerHouseCountry
Indicates that a lower legislative house is associated with or belongs to a particular country.
-
E.
hasNumberOfMPs
Indicates the relationship that specifies how many members of parliament (MPs) are associated with a given entity.
- 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_69f76df8089481909f0018266ee881b7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: May 3, 2026, 4:04 p.m.