Triple
T16918859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Recall |
E410389
|
entity |
| Predicate | numberOfReplacementCandidates |
P39022
|
FINISHED |
| Object | 135 |
—
|
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: 135 | Statement: [The Recall, numberOfReplacementCandidates, 135]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfReplacementCandidates Context triple: [The Recall, numberOfReplacementCandidates, 135]
-
A.
numberOfCandidates
Indicates the total count of candidates associated with a given entity or context.
-
B.
numberOfSubstitutes
chosen
Indicates the quantity of substitute entities associated with or allowed for a given entity or situation.
-
C.
numberOfMajorCandidates
Indicates the count of major candidates associated with a given entity or event.
-
D.
mainCandidates
Indicates that the referenced entities are the primary or most prominent candidates within a given selection or context.
-
E.
numberOfAdditionalMembers
Indicates the count of extra members associated with an entity beyond its primary or standard membership.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdec3d0c8190994a0fca335c65d6 |
completed | April 18, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.