Triple
T7802882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Point Comfort |
E180472
|
entity |
| Predicate | hasHistoricUseSince |
P46987
|
FINISHED |
| Object | 17th 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: 17th century | Statement: [Old Point Comfort, hasHistoricUseSince, 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricUseSince Context triple: [Old Point Comfort, hasHistoricUseSince, 17th century]
-
A.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
B.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
C.
hasHistorySince
Indicates that an entity has maintained a particular state, condition, or relationship continuously starting from a specified point in time.
-
D.
areUsedSince
chosen
Indicates that entities have been in use continuously starting from a specified point in time.
-
E.
hasHistoryPeriod
Indicates that something is associated with, belongs to, or occurs within a specific historical period or era.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:33 p.m.