Triple
T3821413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamer Daron Acemoglu |
E84380
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kamer Daron |
E84380
|
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: Kamer Daron | Statement: [Kamer Daron Acemoglu, givenName, Kamer Daron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamer Daron Context triple: [Kamer Daron Acemoglu, givenName, Kamer Daron]
-
A.
Kamer Daron
chosen
Kamer Daron is the given first name of Daron Acemoglu, a prominent Turkish-American economist known for his work on political economy and institutional development.
-
B.
Green Chamber
The Green Chamber is the main legislative hall of Nigeria’s House of Representatives, where federal lawmakers convene to debate and pass national laws.
-
C.
Throne Room
The Throne Room is a grand ceremonial chamber in the Palace of Holyroodhouse used for royal receptions and state occasions in Scotland.
-
D.
Throne Room
The Throne Room is the grand ceremonial hall of the Royal Palace of Madrid, lavishly decorated and used for state receptions and official royal events.
-
E.
Throne Room
The Throne Room in the Winter Palace is an opulent ceremonial hall where Russian emperors once held court and conducted state functions.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeea62cdfc81909a3bf458b73d60e7 |
completed | March 9, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb4998248190b4174dd80a8e790c |
completed | March 14, 2026, 6:08 a.m. |
Created at: March 9, 2026, 3:17 p.m.