Triple
T38349735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William S. Burroughs as Tom the Priest |
E1041643
|
entity |
| Predicate | actorIs |
P87456
|
FINISHED |
| Object | William S. Burroughs |
—
|
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: William S. Burroughs | Statement: [William S. Burroughs as Tom the Priest, actorIs, William S. Burroughs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actorIs Context triple: [William S. Burroughs as Tom the Priest, actorIs, William S. Burroughs]
-
A.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
-
B.
employedActor
Indicates that one entity has hired or currently employs another entity to perform work or services.
-
C.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
D.
subjectHasActor
Indicates that a subject is associated with or possesses a particular actor involved in an action or process.
-
E.
playsAs
chosen
Indicates that one entity performs, portrays, or assumes the role, character, or persona of another 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.