Triple
T21899424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted (living teddy bear) |
E540767
|
entity |
| Predicate | relationshipWithJohnBennett |
P146101
|
FINISHED |
| Object | childhood friend |
—
|
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: childhood friend | Statement: [Ted (living teddy bear), relationshipWithJohnBennett, childhood friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithJohnBennett Context triple: [Ted (living teddy bear), relationshipWithJohnBennett, childhood friend]
-
A.
relationshipTypeWithJohnLuther
Indicates the specific nature or category of the relationship an entity has with John Luther.
-
B.
relationshipToBenny
Indicates the specific type of personal or social relationship that an entity has with Benny.
-
C.
relationshipToJohnShipton
Indicates the specific familial or social relationship that an entity has to John Shipton.
-
D.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
E.
relationshipWithKat Barton
Indicates the existence or nature of a relationship that an entity has with Kat Barton.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fca2bf88190b2a5b912aa102513 |
completed | April 28, 2026, 8:59 p.m. |
| PD | Predicate disambiguation | batch_69e6be9a65888190a66598d62d20366c |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 7:07 p.m.