Triple
T31515555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owen Warland |
E804063
|
entity |
| Predicate | relationshipToAnnieHovenden |
P207446
|
FINISHED |
| Object | unrequited admirer |
—
|
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: unrequited admirer | Statement: [Owen Warland, relationshipToAnnieHovenden, unrequited admirer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAnnieHovenden Context triple: [Owen Warland, relationshipToAnnieHovenden, unrequited admirer]
-
A.
relationshipToAnne
Indicates the specific familial, social, or interpersonal connection that one entity has to Anne.
-
B.
relationshipToAnnDeever
Indicates the specific interpersonal or familial relationship that an entity has to Ann Deever.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipStatusWithAnna
Indicates the type or state of the relationship that an entity currently has with Anna.
-
E.
relationshipToAnnaPaul
Indicates that one entity has a specified personal or social relationship to Anna Paul.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 9:52 p.m.