Triple
T34822930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faith Lehane |
E1003835
|
entity |
| Predicate | relationshipTypeWith Angel |
P205569
|
FINISHED |
| Object | ally |
—
|
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: ally | Statement: [Faith Lehane, relationshipTypeWith Angel, ally]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Angel Context triple: [Faith Lehane, relationshipTypeWith Angel, ally]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipWithAngelEyes
Indicates a personal or significant connection that an entity has with the individual referred to as AngelEyes.
-
C.
relationshipTypeWithTiamat
Indicates the specific nature or category of relationship an entity has with Tiamat.
-
D.
relationshipTypeStart
Indicates the type or category of relationship that begins or is initiated at a specific point or event.
-
E.
relationshipToBond
Indicates the specific type of personal, familial, or professional relationship an entity has to the person named Bond.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.