Triple
T17296715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haga Park palace complex |
E419929
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Haga Park |
E115109
|
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: Haga Park | Statement: [Haga Park palace complex, hasComponent, Haga Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haga Park Context triple: [Haga Park palace complex, hasComponent, Haga Park]
-
A.
Haga Park
chosen
Haga Park is a historic royal park in the Stockholm area known for its landscaped grounds, cultural heritage sites, and recreational green spaces.
-
B.
Daewangam Park
Daewangam Park is a coastal park in Ulsan, South Korea, known for its dramatic seaside cliffs, pine forest trails, and views of the Daewangam Rock formation.
-
C.
Taejongdae Park
Taejongdae Park is a scenic coastal park in Busan, South Korea, famous for its dramatic seaside cliffs, lighthouse views, and walking trails overlooking the ocean.
-
D.
Neahwa Park
Neahwa Park is a public recreational park in Oneonta, New York, featuring open green spaces, sports facilities, and community gathering areas.
-
E.
Yongdusan Park
Yongdusan Park is a popular hilltop park in Busan, South Korea, known for its scenic city and harbor views, walking paths, and the iconic Busan Tower.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437881d688190a633beacba6bc0ae |
completed | April 19, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180d881ec81908e794143d355effe |
completed | May 11, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:40 a.m.