Triple
T10615602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlington, Iowa |
E276109
|
entity |
| Predicate | Snake AlleyCharacterization |
P94988
|
FINISHED |
| Object | famously steep and winding street |
—
|
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: famously steep and winding street | Statement: [Burlington, Iowa, Snake AlleyCharacterization, famously steep and winding street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Snake AlleyCharacterization Context triple: [Burlington, Iowa, Snake AlleyCharacterization, famously steep and winding street]
-
A.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
B.
The Snake Pit_is
Indicates that something is identified as, classified as, or described as "The Snake Pit."
-
C.
characterAlias
Indicates that one character is known or referred to by an alternative name or alias.
-
D.
nightlifeCharacter
Indicates a characteristic or quality associated with nightlife, such as the typical atmosphere, energy, or style of nighttime social activities.
-
E.
cityQuarterCharacter
Indicates the characteristic qualities or distinctive nature that define a particular city quarter.
- F. None of above. chosen
Provenance (4 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df6d76dc8190bd8d481fed3225d9 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7a223c8190854409d76368f3e8 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 7:33 p.m.