Triple
T16130927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaleiçi |
E391393
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Hıdırlık Tower |
E86550
|
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: Hıdırlık Tower | Statement: [Kaleiçi, hasPart, Hıdırlık Tower]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hıdırlık Tower Context triple: [Kaleiçi, hasPart, Hıdırlık Tower]
-
A.
Hıdırlık Tower
chosen
Hıdırlık Tower is an ancient Roman-era stone tower and prominent coastal landmark overlooking the harbor in Antalya, Turkey.
-
B.
Heron Tower
Heron Tower is a prominent modern office skyscraper in the City of London, known for its glass façade and status as one of the tallest buildings in the UK capital.
-
C.
Phoenix Tower
Phoenix Tower is a historic pavilion within the Mukden Palace complex in Shenyang, China, notable for its traditional Qing dynasty architecture and ceremonial significance.
-
D.
Mihulka Tower
Mihulka Tower is a historic fortification tower in Prague, Czech Republic, that once formed part of the city’s medieval defensive system and later served various military and scientific purposes.
-
E.
Trident Tower
Trident Tower is a major multi-slide water attraction featuring high-speed rides and thrilling drops at Dubai’s Aquaventure Waterpark.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020829e88190b51ab32d22cf0259 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2aff07c8190bf693f652e2a2808 |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5:01 a.m.