Triple
T3647645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecca De Mornay |
E77339
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | ER (TV series) |
E82125
|
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: ER (TV series) | Statement: [Rebecca De Mornay, notableWork, ER (TV series)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ER (TV series) Context triple: [Rebecca De Mornay, notableWork, ER (TV series)]
-
A.
ER3
ER3 is the IATA aircraft type code used to designate the Embraer ERJ 135 regional jet.
-
B.
Rede
Rede is a small rural village and civil parish in Suffolk, England, characterized by its historic countryside setting and traditional English village features.
-
C.
ER
ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
-
D.
ER
chosen
ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
-
E.
ER
ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc38aa2388190bf1af926375e2433 |
completed | March 8, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f394f9c8190881edc18b544dbb7 |
completed | March 13, 2026, 5:54 p.m. |
Created at: March 8, 2026, 3:24 p.m.