Triple
T16647634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smog |
E404511
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | (Smog) |
E16362
|
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: (Smog) | Statement: [Smog, alsoKnownAs, (Smog)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: (Smog) Context triple: [Smog, alsoKnownAs, (Smog)]
-
A.
Smog
chosen
Smog is the lo-fi indie rock project of American singer-songwriter Bill Callahan, known for its sparse arrangements and introspective, deadpan lyricism.
-
B.
Haze
Haze is the surname of Dolores "Lolita" Haze, the fictional adolescent protagonist of Vladimir Nabokov’s novel "Lolita."
-
C.
Fog
"Fog" is a brief, imagistic poem by Carl Sandburg that famously compares fog to a silent cat, exemplifying his modern, accessible style.
-
D.
Niebla
Niebla is a landmark 1914 novel by Spanish writer Miguel de Unamuno that blends fiction and philosophy in a metafictional exploration of identity, free will, and the nature of literary creation.
-
E.
Niebla
Niebla is a historic town in the province of Huelva, Spain, known for its well-preserved medieval walls and strategic importance in Andalusian history.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad66fe88190be582b81719f2ac1 |
completed | April 18, 2026, 12:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00aaeaf4388190aa5340a01938b3f2 |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 5:18 a.m.