Triple
T16665144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honolulu street network |
E404963
|
entity |
| Predicate | organizedAround |
P46126
|
FINISHED |
| Object | Waikiki |
E16766
|
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: Waikiki | Statement: [Honolulu street network, organizedAround, Waikiki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waikiki Context triple: [Honolulu street network, organizedAround, Waikiki]
-
A.
Waikiki
chosen
Waikiki is a famous beachfront neighborhood in Honolulu renowned for its white-sand beaches, surf culture, and major tourist resorts.
-
B.
Waikiki
Waikiki is a coastal suburb in the City of Rockingham, Western Australia, known for its residential areas and proximity to sandy beaches.
-
C.
Hualālai
Hualālai is an active shield volcano on the western side of Hawaiʻi Island, known for its relatively recent eruptions and luxury resort developments on its flanks.
-
D.
Mākaha Beach
Mākaha Beach is a renowned surfing and snorkeling beach on Oahu’s west (Leeward) coast, known for its powerful winter waves and clear, calm waters in summer.
-
E.
Haleiwa
Haleiwa is a historic surf town on Oahu’s North Shore in Hawaii, known for its laid-back atmosphere, beaches, and local shops and eateries.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9be0688190afda306cde934c68 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a32988c8190a671a4cbd829047a |
completed | May 10, 2026, 1:37 p.m. |
Created at: April 10, 2026, 5:18 a.m.