Triple
T32064464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doug Harris |
E818835
|
entity |
| Predicate | hasNoRealGroomsmen |
P202991
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Doug Harris, hasNoRealGroomsmen, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoRealGroomsmen Context triple: [Doug Harris, hasNoRealGroomsmen, true]
-
A.
hasGroom
Indicates that an entity has a groom, i.e., is associated with a male partner in a marriage or wedding relationship.
-
B.
hasNotableCelebrant
Indicates that an entity (such as an event, holiday, or occasion) is associated with a specific person or group who is prominently recognized for celebrating or observing it.
-
C.
hasGroomFather
Indicates that a person serves as the father of the groom in a marriage-related relationship.
-
D.
hasPublicCeremony
Indicates that a public ceremony is held or conducted in relation to the subject entity.
-
E.
guestAtWedding
Indicates that a person is attending or has attended a particular wedding as a guest.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00d8ba18808190976682088a02a9a8 |
completed | May 10, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_6a00d85fad64819084f424ec8ecd3b57 |
completed | May 10, 2026, 7:11 p.m. |
| PDg | Predicate description generation | batch_6a00d8b8eac08190809c78998e09c47c |
completed | May 10, 2026, 7:12 p.m. |
Created at: May 1, 2026, 12:22 a.m.