Triple
T1504768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastham |
E33873
|
entity |
| Predicate | hasTransportHistoryAs |
P29445
|
FINISHED |
| Object | transport hub |
—
|
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: transport hub | Statement: [Eastham, hasTransportHistoryAs, transport hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportHistoryAs Context triple: [Eastham, hasTransportHistoryAs, transport hub]
-
A.
ownershipHistory
Indicates the sequence of past and present owners associated with an entity over time.
-
B.
hasPolicyHistory
Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
-
C.
hasDenominationHistory
Indicates that an entity has an associated record or sequence of changes in its denomination over time.
-
D.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
E.
hasFireHistory
Indicates that an entity has experienced one or more fire events in the past.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a90582f2548190bc0a6bdcd6d9d015 |
completed | March 5, 2026, 4:24 a.m. |
Created at: March 4, 2026, 7:24 p.m.