Triple
T9886205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Crane |
E180936
|
entity |
| Predicate | homeCityInBackstory |
P91611
|
FINISHED |
| Object | Seattle Police Department jurisdiction |
—
|
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: Seattle Police Department jurisdiction | Statement: [Martin Crane, homeCityInBackstory, Seattle Police Department jurisdiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCityInBackstory Context triple: [Martin Crane, homeCityInBackstory, Seattle Police Department jurisdiction]
-
A.
homeCityInStory
Indicates that a specified city serves as a character’s home city within the context of a particular story.
-
B.
homeCityMetropolitanArea
Indicates that a specified city serves as the primary metropolitan area associated with a given entity’s home location.
-
C.
homeCitySince
Indicates the city that has served as an entity’s home starting from a specified point in time.
-
D.
nativeCity
Indicates that a city is the place where a person was born or is originally from.
-
E.
homeTownType
Indicates the type or classification of a person's hometown (e.g., city, village, suburb).
- 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_69ca828082cc8190a40f8d299caa6545 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb45659748190a3ebd1abe23c8779 |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:38 p.m.