Triple
T13782945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rawhide |
E331174
|
entity |
| Predicate | firstUsedAsThemeInYear |
P111447
|
FINISHED |
| Object | 1959 |
—
|
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: 1959 | Statement: [Rawhide, firstUsedAsThemeInYear, 1959]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUsedAsThemeInYear Context triple: [Rawhide, firstUsedAsThemeInYear, 1959]
-
A.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
-
B.
firstVersionYear
Indicates the calendar year in which the first version or initial release of something was created, published, or made available.
-
C.
introducedInYear
Indicates the year in which something was first introduced, launched, or made available.
-
D.
introducedInTheme
Indicates that something (such as a concept, character, or element) is first presented or brought into use within a particular theme.
-
E.
firstCreationYear
Indicates the year in which something was first created or originally produced.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0247ccc881908dad7b547221f15d |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:11 p.m.