Triple
T16966818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playboy Clubs |
E411560
|
entity |
| Predicate | firstLocationOpeningDate |
P125421
|
FINISHED |
| Object | 1960 |
—
|
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: 1960 | Statement: [Playboy Clubs, firstLocationOpeningDate, 1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLocationOpeningDate Context triple: [Playboy Clubs, firstLocationOpeningDate, 1960]
-
A.
firstLineOpeningDate
Indicates the date on which the first line in a system, network, or service was officially opened or began operation.
-
B.
officialOpeningDate
Indicates the calendar date on which something is formally inaugurated or officially opened for use or operation.
-
C.
firstOpenedAt
Indicates the date and time at which something was initially opened for the first time.
-
D.
officialOpeningYear
Indicates the calendar year in which something was formally opened or inaugurated for official use.
-
E.
openedFirstBoutiqueIn
Indicates that an entity established its first boutique or retail store in a specified location.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a548b48190b87468630f3e3209 |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:31 a.m.