Triple
T15646996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Keller |
E376204
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object | Dani |
E377765
|
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: Dani | Statement: [Rachel Keller, playedCharacter, Dani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dani Context triple: [Rachel Keller, playedCharacter, Dani]
-
A.
Dani
chosen
Dani is a fictional character played by actress Adria Arjona, known from her role in the fantasy-romance film "Emerald City" and other screen appearances.
-
B.
Dani
The Dani are an indigenous ethnic group of the central highlands of Papua, Indonesia, known for their distinctive traditional dress, terraced agriculture, and complex ritual practices.
-
C.
Dani
Dani is the given name of Dani Rodrik, a prominent Turkish economist known for his work on globalization and economic development.
-
D.
DON
DON is the vehicle registration code used on license plates for vehicles registered in the Donauwörth area of Germany.
-
E.
DON
DON is the Seattle Department of Neighborhoods, a city agency that works to engage residents, strengthen communities, and support neighborhood-based initiatives.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67936e388190913c9060194e5b53 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:15 a.m.