Triple
T33464856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Gargery |
E857017
|
entity |
| Predicate | relationshipToPip |
P204043
|
FINISHED |
| Object | brother-in-law |
—
|
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: brother-in-law | Statement: [Joe Gargery, relationshipToPip, brother-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPip Context triple: [Joe Gargery, relationshipToPip, brother-in-law]
-
A.
relationshipWithPip
chosen
Indicates that one entity has some form of relationship or association with an entity referred to as Pip.
-
B.
relationshipToPlayer
Indicates the type of personal or social connection an entity has with the player.
-
C.
relationshipToParent
Indicates the specific familial or social role an entity has in relation to its parent entity.
-
D.
relationToBPP
Indicates the specific type of relationship or association an entity has to a designated BPP (e.g., as owner, member, participant, or related party).
-
E.
relationshipToHost
Indicates the type or nature of the connection, association, or role that one entity has in relation to a host 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:37 a.m.