Triple
T38632280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rancho Ex-Mission San Fernando (lease/interest) |
E937480
|
entity |
| Predicate | hasLessee |
P198180
|
FINISHED |
| Object | Pío Pico |
—
|
NE NERFINISHED |
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: Pío Pico | Statement: [Rancho Ex-Mission San Fernando (lease/interest), hasLessee, Pío Pico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLessee Context triple: [Rancho Ex-Mission San Fernando (lease/interest), hasLessee, Pío Pico]
-
A.
lessor
Indicates a party that grants another party the right to use an asset or property, typically in exchange for payment, under a lease agreement.
-
B.
leaseStatus
Indicates the current state or condition of a lease agreement, such as whether it is active, pending, expired, or terminated.
-
C.
wasLeasedFor
Indicates that one entity was leased in exchange for a specified payment amount, purpose, or consideration.
-
D.
ownsOrLeases
Indicates that one entity has legal rights to use or control another entity either through ownership or through a lease agreement.
-
E.
hasLeisureTenant
Indicates that an entity has another entity as a tenant specifically for leisure-related use or activities.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
| PDg | Predicate description generation | batch_69feced436a48190b761db7df2d6b6bd |
completed | May 9, 2026, 6:06 a.m. |
Created at: May 3, 2026, 4:32 p.m.