Triple
T38674095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Balfour |
E943680
|
entity |
| Predicate | caseAlsoKnownAs |
P191512
|
FINISHED |
| Object | Hudson family murders |
—
|
NE NERFINISHED |
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: Hudson family murders | Statement: [William Balfour, caseAlsoKnownAs, Hudson family murders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseAlsoKnownAs Context triple: [William Balfour, caseAlsoKnownAs, Hudson family murders]
-
A.
alsoKnownAs
Indicates that one entity is an alternative name, alias, or designation for another entity.
-
B.
knownAsBy
Indicates that one entity is referred to or recognized by another entity using a particular name or designation.
-
C.
isPartlyKnownAs
Indicates that an entity is known by a particular name or label in some, but not all, contexts or sources.
-
D.
knownAsOneOf
Indicates that an entity is recognized or referred to as one member of a specified set of alternative names, labels, or identities.
-
E.
alsoKnownThrough
Indicates that an entity is recognized or identified by means of another entity, such as a source, context, or intermediary, through which its alternative name or identity is known.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:33 p.m.