Triple
T26155561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rubberneck |
E659947
|
entity |
| Predicate | hasWorkplaceSetting |
P115811
|
FINISHED |
| Object | laboratory |
—
|
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: laboratory | Statement: [Rubberneck, hasWorkplaceSetting, laboratory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkplaceSetting Context triple: [Rubberneck, hasWorkplaceSetting, laboratory]
-
A.
hasWorkAsSetting
Indicates that a particular work (such as a story, film, or artwork) takes place in or uses a specified location, time, or environment as its setting.
-
B.
workSetting
Indicates the environment, context, or conditions in which the work or activity is carried out.
-
C.
associatedWithWorkplace
Indicates a relationship where an entity has a connection or affiliation with a particular workplace or place of employment.
-
D.
hasProfessionSetting
Indicates that an entity’s professional activity or role is carried out within a particular setting or environment.
-
E.
worksInSetting
chosen
Indicates that an entity performs its activities or functions within a specified environment, context, or setting.
- 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_69ee5bc5a9908190899d39ce95c6d215 |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 26, 2026, 8:27 p.m.