Triple
T13405268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAI Madrid Department |
E319937
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | DAI |
E82832
|
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: DAI | Statement: [DAI Madrid Department, partOf, DAI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DAI Context triple: [DAI Madrid Department, partOf, DAI]
-
A.
DAI
chosen
DAI is the commonly used abbreviation for the German Archaeological Institute, a leading international institution for archaeological research and cultural heritage preservation.
-
B.
DAI
DAI is a prominent fine arts museum in Dayton, Ohio, known for its diverse art collections, educational programs, and cultural exhibitions.
-
C.
Dai
Dai is a common Welsh given name, often used as a familiar or diminutive form of David.
-
D.
Dai
The Dai are an ethnic group in southern China and Southeast Asia, culturally related to the Thai and Lao peoples and known for their Theravada Buddhist traditions, distinctive festivals, and stilted wooden houses.
-
E.
DA
DA is the vehicle registration code for the German city of Darmstadt and its surrounding district in the state of Hesse.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4ae47081909b68a9aaa62fd4c7 |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307904608190ad647f741c08dc42 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:34 p.m.