Triple
T36717416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne Gale |
E906949
|
entity |
| Predicate | relationshipToMickeyKnox |
P205017
|
FINISHED |
| Object | media exploiter |
—
|
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: media exploiter | Statement: [Wayne Gale, relationshipToMickeyKnox, media exploiter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMickeyKnox Context triple: [Wayne Gale, relationshipToMickeyKnox, media exploiter]
-
A.
relationshipToMickey
Indicates the specific familial, social, or other personal connection that one entity has to Mickey.
-
B.
relationshipTypeWithMarvin
Indicates the specific nature or category of the relationship an entity has with Marvin.
-
C.
relationshipToMike
Indicates the specific type of personal, social, or familial relationship that an entity has with Mike.
-
D.
relationshipToKenny
Indicates the specific familial, social, or interpersonal connection that one entity has to Kenny.
-
E.
relationshipToLloyd
Indicates the specific type of personal or social relationship an entity has with Lloyd.
- 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_69f76e73ad108190a5241585f2303e9a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:12 p.m.