Triple
T13372268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wyman |
E319093
|
entity |
| Predicate | hasWorkTypeContext |
P104843
|
FINISHED |
| Object | analytic philosophy essay |
—
|
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: analytic philosophy essay | Statement: [Wyman, hasWorkTypeContext, analytic philosophy essay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkTypeContext Context triple: [Wyman, hasWorkTypeContext, analytic philosophy essay]
-
A.
hasWorkContext
Indicates that an entity is associated with a particular work-related situation, environment, or context in which it is relevant or applies.
-
B.
hasWorkTypeRelation
chosen
Indicates a relationship specifying the type or category of work associated with an entity.
-
C.
hasRoleInWorkType
Indicates that an entity holds a specific role or function within a particular type or category of work.
-
D.
hasTaskType
Indicates that an entity is associated with or classified under a specific type or category of task.
-
E.
hasWorkCount
Indicates the number of works (such as items, creations, or outputs) associated with a given entity.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd8950481909785a2060f43b6ed |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.