Triple
T1447022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master Settlement Agreement |
E31200
|
entity |
| Predicate | numberOfStatesSigning |
P4946
|
FINISHED |
| Object | 46 |
—
|
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: 46 | Statement: [Master Settlement Agreement, numberOfStatesSigning, 46]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStatesSigning Context triple: [Master Settlement Agreement, numberOfStatesSigning, 46]
-
A.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
B.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
C.
numberOfSignatories
chosen
Indicates the total count of entities that have formally signed or endorsed a given document, agreement, or item.
-
D.
numberOfMemberStates
Indicates the total count of member states associated with a given entity or organization.
-
E.
signatoryState
Indicates that a state is a formal party to, and has signed or ratified, a specific treaty, agreement, or legal instrument.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c558e0e081909802753872374d7b |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.