Triple
T13080169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The First Third |
E310179
|
entity |
| Predicate | hasNotableSetting |
P3538
|
FINISHED |
| Object | Denver skid row |
—
|
LITERAL 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: Denver skid row | Statement: [The First Third, hasNotableSetting, Denver skid row]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSetting Context triple: [The First Third, hasNotableSetting, Denver skid row]
-
A.
hasNotableSettingBy
Indicates that the subject has a notable or significant setting that was created, designed, or established by the specified entity.
-
B.
notableSetting
Indicates that a particular place or environment is especially significant or prominent as the context in which an entity is situated or occurs.
-
C.
hasSetting
chosen
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
D.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
E.
hasNotablePolicy
Indicates that an entity possesses a policy that is distinguished, significant, or otherwise noteworthy in its context.
- F. None of above.
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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d98119cb7081908b78ffe83ec99851 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:01 p.m.