Triple
T3374046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Egan |
E71022
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Manhattan Beach |
E204033
|
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: Manhattan Beach | Statement: [Jennifer Egan, notableWork, Manhattan Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manhattan Beach Context triple: [Jennifer Egan, notableWork, Manhattan Beach]
-
A.
Manhattan Beach
Manhattan Beach is a coastal city in Southern California known for its sandy beaches, beach volleyball, and upscale yet laid-back seaside community.
-
B.
Manhattan Beach
chosen
Manhattan Beach is a residential neighborhood and popular oceanfront beach area in southern Brooklyn, New York City, known for its park, shoreline, and family-oriented atmosphere.
-
C.
Bayhead
Bayhead is a small rural settlement on the island of North Uist in Scotland's Outer Hebrides.
-
D.
Seaside
Seaside is a coastal city in Monterey County, California, known for its proximity to Monterey Bay and California State University, Monterey Bay.
-
E.
Seaside
Seaside is a popular resort city on the northern Oregon Coast known for its sandy beaches, historic promenade, and family-friendly attractions.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bf4ad88190a2c49dc30f323a13 |
completed | March 8, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33442f28c8190b48a662a5dd1bac3 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.