Triple
T23015966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charter 08 |
E573029
|
entity |
| Predicate | numberOfSignatoriesBy2009 |
P4946
|
FINISHED |
| Object | thousands |
—
|
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: thousands | Statement: [Charter 08, numberOfSignatoriesBy2009, thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSignatoriesBy2009 Context triple: [Charter 08, numberOfSignatoriesBy2009, thousands]
-
A.
numberOfSignatories
chosen
Indicates the total count of entities that have formally signed or endorsed a given document, agreement, or item.
-
B.
womenSignatoriesCount
Indicates the number of women who are signatories in a given agreement, document, or context.
-
C.
hasSignatories
Indicates that one or more parties have formally signed or endorsed an agreement, document, or instrument.
-
D.
estimatedNumberOfSignatures
Indicates the approximate count of signatures associated with or required for a given item, action, or agreement.
-
E.
laterSignatoriesCount
Indicates the number of other entities that became signatories after the referenced 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e4dcd48190b2b1c2ab43205e41 |
completed | April 29, 2026, 4:07 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:51 p.m.