Triple
T29493098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Weber |
E748136
|
entity |
| Predicate | homeTownSetting |
P81759
|
FINISHED |
| Object | Salem's Lot |
—
|
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: Salem's Lot | Statement: [Joe Weber, homeTownSetting, Salem's Lot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeTownSetting Context triple: [Joe Weber, homeTownSetting, Salem's Lot]
-
A.
homeTownType
Indicates the type or classification of a person's hometown (e.g., city, village, suburb).
-
B.
homeCityInStory
chosen
Indicates that a specified city serves as a character’s home city within the context of a particular story.
-
C.
homeCityInBackstory
Indicates that an entity has a specified city as its home city within its narrative or character backstory.
-
D.
homeCityOf
Indicates that a particular city is the primary place of residence or origin for a given person or organization.
-
E.
homeLocationInStory
Indicates the place that serves as a character’s primary home or base of residence within the context of the story.
- F. None of above.
Provenance (3 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_69f0bd448c6881908aa6b475cefd5ddc |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 4:16 p.m.