Triple
T20478490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmen |
E502386
|
entity |
| Predicate | hasPet |
P8711
|
FINISHED |
| Object | Freeway |
—
|
NE NERFINISHED |
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: Freeway | Statement: [Carmen, hasPet, Freeway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freeway Context triple: [Carmen, hasPet, Freeway]
-
A.
Freeway
Freeway is a 1996 darkly comedic crime thriller film loosely based on "Little Red Riding Hood," known for its gritty tone and subversive take on fairy-tale tropes.
-
B.
Freeway
chosen
Freeway is the beloved pet dog in the television series "Hart to Hart," often accompanying the main characters Jonathan and Jennifer Hart on their adventures.
-
C.
Freeway
Freeway is a classic 1981 Atari 2600 video game, co-created by David Crane, in which players guide chickens across multiple lanes of traffic.
-
D.
Freeway
Freeway is an American rapper from Philadelphia known for his gritty street narratives and work with Roc-A-Fella Records and State Property.
-
E.
Freeway 1
Freeway 1 is a major north–south expressway in Taiwan that connects key urban areas, including parts of New Taipei City such as Sanchong District.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b54c8188190a71e35fab8d194a6 |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.