Triple
T9826508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muni Metro K Ingleside line |
E238666
|
entity |
| Predicate | designation |
P38
|
FINISHED |
| Object | K |
E722054
|
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: K | Statement: [Muni Metro K Ingleside line, designation, K]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K Context triple: [Muni Metro K Ingleside line, designation, K]
-
A.
K
K is the line designation used for Los Angeles Metro's K Line light rail service.
-
B.
K
K is the replicant blade runner protagonist of the science fiction film "Blade Runner 2049," whose investigation into a long-buried secret drives the movie’s central mystery and themes of identity.
-
C.
K
chosen
K is the route designation for San Francisco’s Muni Metro K Ingleside light rail line.
-
D.
K.
K. is the enigmatic land surveyor protagonist of Franz Kafka’s novel "The Castle," whose futile attempts to gain access to the mysterious authorities embody themes of alienation and bureaucratic absurdity.
-
E.
Ka
Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb32370e8819087c85fb8328587be |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc88a86c819088f259a049eec4db |
completed | April 5, 2026, 2:44 a.m. |
Created at: March 30, 2026, 8:32 p.m.