Triple
T25866310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiki the parrot |
E651624
|
entity |
| Predicate | relationshipToJackTrent |
P125661
|
FINISHED |
| Object | sidekick |
—
|
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: sidekick | Statement: [Kiki the parrot, relationshipToJackTrent, sidekick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToJackTrent Context triple: [Kiki the parrot, relationshipToJackTrent, sidekick]
-
A.
relationshipToJack
chosen
Indicates the specific type of personal or social connection an entity has with Jack.
-
B.
relationshipToJackBrown
Indicates the specific familial, social, or professional relationship that an entity has to Jack Brown.
-
C.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
-
D.
relationshipTypeWithJackieTaylor
Indicates the specific type or nature of the relationship that an entity has with Jackie Taylor.
-
E.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
- 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
Created at: April 22, 2026, 8:07 a.m.