Triple
T2466299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dead Horse Bay |
E55255
|
entity |
| Predicate | hasTypeOfDebris |
P1845
|
FINISHED |
| Object | glass bottles from early 20th century |
—
|
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: glass bottles from early 20th century | Statement: [Dead Horse Bay, hasTypeOfDebris, glass bottles from early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfDebris Context triple: [Dead Horse Bay, hasTypeOfDebris, glass bottles from early 20th century]
-
A.
debrisFieldStates
Indicates the various conditions or statuses associated with a particular debris field over time or in a given context.
-
B.
hasTypeOfWreck
Indicates that one entity is classified as a specific type or category of wreck (e.g., shipwreck, car wreck) associated with another entity.
-
C.
hasSedimentsThat
Indicates that one entity contains, includes, or is associated with specific sediments described by the related entity.
-
D.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
E.
typeOfDam
Indicates the specific kind or classification of a dam associated with an entity.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.