Triple
T15959722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Innes |
E387025
|
entity |
| Predicate | appearedInTVSeries |
P795
|
FINISHED |
| Object | ER |
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 | Statement: [Laura Innes, appearedInTVSeries, ER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ER Context triple: [Laura Innes, appearedInTVSeries, ER]
-
A.
ER
ER is the zone code for Eastern Railway, one of the major railway zones of Indian Railways headquartered in Kolkata.
-
B.
ER
ER is the abbreviation used to designate the Eastern Region of British Rail, a major administrative division of the former British railway network covering eastern England.
-
C.
ER
ER is the standard abbreviation used for the Erie Otters, a junior ice hockey team in the Ontario Hockey League.
-
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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fe82d081908b5d41bc5a709de2 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3c3aae081909366c01b3fec4d47 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:53 a.m.