Triple
T9854672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Martin Brenner |
E239553
|
entity |
| Predicate | relationshipToEleven |
P38921
|
FINISHED |
| Object | surrogate father |
—
|
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: surrogate father | Statement: [Dr. Martin Brenner, relationshipToEleven, surrogate father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEleven Context triple: [Dr. Martin Brenner, relationshipToEleven, surrogate father]
-
A.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
B.
relationshipToGreenBayPackers
Indicates the nature of a person or entity’s connection or association with the Green Bay Packers.
-
C.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
D.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
E.
relationshipToEvanHansen
Indicates the type or nature of a person's relationship or connection to Evan Hansen.
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3960fb481909c90d6d6cafc6222 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:34 p.m.