Triple
T9866160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paladin |
E239836
|
entity |
| Predicate | oftenHelps |
P90956
|
FINISHED |
| Object | people in trouble |
—
|
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: people in trouble | Statement: [Paladin, oftenHelps, people in trouble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenHelps Context triple: [Paladin, oftenHelps, people in trouble]
-
A.
especiallyHelpsWhen
Indicates that one entity is particularly beneficial or effective in assisting another entity or situation under certain conditions or circumstances.
-
B.
oftenProvides
Indicates that one entity frequently or regularly supplies, offers, or makes another entity available.
-
C.
helpedCause
Indicates that one entity contributed to bringing about, enabling, or facilitating an outcome or event involving another entity.
-
D.
oftenSays
Indicates that one entity frequently makes a particular statement or remark, or regularly expresses a certain idea or phrase.
-
E.
oftenRefersTo
Indicates that one entity is frequently used to mention, denote, or reference another entity in common usage or context.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d091e48190b10463562d0dc461 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:36 p.m.