Triple
T21841619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitty Forman |
E539265
|
entity |
| Predicate | relationshipToEricForman |
P145525
|
FINISHED |
| Object | mother |
—
|
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: mother | Statement: [Kitty Forman, relationshipToEricForman, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEricForman Context triple: [Kitty Forman, relationshipToEricForman, mother]
-
A.
relationshipToElaineBenes
Indicates a person's specific relational connection (such as friend, partner, or family member) to Elaine Benes.
-
B.
relationshipToEvanHansen
Indicates the type or nature of a person's relationship or connection to Evan Hansen.
-
C.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
D.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
E.
relationshipToPete
Indicates the specific type of relationship or connection that an entity has to Pete.
- 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7acb17c81908c0de0afac5a9fa7 |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c187bc548190b4ca13150f6bae38 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 6:55 p.m.