Triple
T27966973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Took a Pill in Ibiza |
E704751
|
entity |
| Predicate | settingMentioned |
P171444
|
FINISHED |
| Object | Ibiza |
—
|
NE NERFINISHED |
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: Ibiza | Statement: [I Took a Pill in Ibiza, settingMentioned, Ibiza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingMentioned Context triple: [I Took a Pill in Ibiza, settingMentioned, Ibiza]
-
A.
mentionedAs
Indicates that one entity is referred to or cited by name or description in the context of another entity.
-
B.
mentionsSee
Indicates that one entity explicitly refers to or cites another entity within its content.
-
C.
mentionedWith
Indicates that two entities are mentioned together or in close association within the same context, such as a document, sentence, or conversation.
-
D.
mentions
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
-
E.
eraMentioned
Indicates that a specific historical or temporal era is explicitly referenced or mentioned in a given 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 7:35 p.m.