Triple
T10629222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Arlen |
E250406
|
entity |
| Predicate | coWrote |
P7732
|
FINISHED |
| Object | Alamo Bay |
E877710
|
NE 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: Alamo Bay | Statement: [Alice Arlen, coWrote, Alamo Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alamo Bay Context triple: [Alice Arlen, coWrote, Alamo Bay]
-
A.
Alamo Bay
chosen
Alamo Bay is a 1985 American drama film that explores racial tensions and conflict in a Texas Gulf Coast fishing community.
-
B.
Mission Bay
Mission Bay is a major University of California, San Francisco campus and research hub in San Francisco known for its focus on biomedical sciences and biotechnology.
-
C.
Mission Bay
Mission Bay is a coastal recreational area in San Diego known for its large aquatic park, beaches, and water sports.
-
D.
Chula Vista Bayfront
Chula Vista Bayfront is a coastal waterfront area in Chula Vista, California, known for its marinas, parks, recreational amenities, and planned mixed-use development along San Diego Bay.
-
E.
Alameda Marina
Alameda Marina is a waterfront harbor and boating facility in Alameda, California, offering slips, marine services, and bay access for recreational and commercial vessels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d988474cf0819087516026fd249640 |
completed | April 10, 2026, 11:31 p.m. |
Created at: April 8, 2026, 9 p.m.