Triple
T21673903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forty Licks |
E534918
|
entity |
| Predicate | spansYears |
P98851
|
FINISHED |
| Object | 1964–2002 |
—
|
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: 1964–2002 | Statement: [Forty Licks, spansYears, 1964–2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spansYears Context triple: [Forty Licks, spansYears, 1964–2002]
-
A.
coversYearsTo
chosen
Indicates a temporal relationship where one entity spans, includes, or extends up to a specified year or range of years represented by the other entity.
-
B.
seasonSpan
Indicates the time period or range of dates over which a particular season extends or is in effect.
-
C.
durationInYears
Indicates the length of time associated with something, measured in whole or fractional years.
-
D.
appliesInYears
Indicates that something (such as a rule, condition, or effect) is valid, relevant, or in force during specific years.
-
E.
countsYearsFrom
Indicates a temporal relationship where the number of years is measured starting from a specified reference point or event.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a0e06688190a75ea29534f5eed3 |
completed | April 27, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:41 p.m.