Triple
T11408362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Maryland |
E270297
|
entity |
| Predicate | firstSettlementFounded |
P89141
|
FINISHED |
| Object | 1634 |
—
|
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: 1634 | Statement: [Province of Maryland, firstSettlementFounded, 1634]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSettlementFounded Context triple: [Province of Maryland, firstSettlementFounded, 1634]
-
A.
firstModernSettlementEstablished
chosen
Indicates that the subject is the location where the earliest modern-era settlement was founded or established.
-
B.
colonyFounded
Indicates that an entity established or created a colony at a particular time or place.
-
C.
firstPermanentSettler
Indicates that the subject is the earliest individual or group to establish a lasting, continuous residence in the location or entity specified by the object.
-
D.
cityFoundedAround
Indicates that a city was established approximately at, but not exactly on, a specified time or period.
-
E.
majorCityFounded
Indicates that one entity is a major city and the other is the date or event of its founding.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014e72748190a01bde2f0105cedb |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.