Triple
T14119300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Whale Who Wanted to Sing at the Met |
E339862
|
entity |
| Predicate | isSegmentNumber |
P8879
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [The Whale Who Wanted to Sing at the Met, isSegmentNumber, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSegmentNumber Context triple: [The Whale Who Wanted to Sing at the Met, isSegmentNumber, 10]
-
A.
hasTypicalSegmentNumber
Indicates that an entity is characterized by a usual or standard number of segments it possesses.
-
B.
isSectionNumber
chosen
Indicates that one entity is the section number identifier associated with another entity, typically within a structured document or text.
-
C.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
D.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
E.
isNumbered
Indicates that an entity has been assigned a specific number or position in an ordered sequence.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de609322ac8190bb389ca250882af5 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.