Triple
T375983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greatest Love of All |
E8373
|
entity |
| Predicate | WhitneyHoustonVersion.length |
P13095
|
FINISHED |
| Object | about 4 minutes 50 seconds |
—
|
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: about 4 minutes 50 seconds | Statement: [Greatest Love of All, WhitneyHoustonVersion.length, about 4 minutes 50 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WhitneyHoustonVersion.length Context triple: [Greatest Love of All, WhitneyHoustonVersion.length, about 4 minutes 50 seconds]
-
A.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
-
B.
numberOfTracks
Indicates the quantity of tracks associated with a given entity.
-
C.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
-
D.
hasVocalDuet
Indicates that two entities perform or participate together in a vocal duet.
-
E.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec169a848190a577aa093c878839 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ebcb1b2c8190a68bb3bad600c227 |
completed | Feb. 28, 2026, 1:21 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.