Triple
T8511289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langley Falls Mall |
E201457
|
entity |
| Predicate | hasFictionalOwnerStatus |
P62301
|
FINISHED |
| Object | privately owned mall (implied in series) |
—
|
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: privately owned mall (implied in series) | Statement: [Langley Falls Mall, hasFictionalOwnerStatus, privately owned mall (implied in series)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalOwnerStatus Context triple: [Langley Falls Mall, hasFictionalOwnerStatus, privately owned mall (implied in series)]
-
A.
hasFictionalProprietor
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative context.
-
B.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
C.
ownedByFictionalCharacter
chosen
Indicates that something is possessed or owned by a fictional (not real-world) character.
-
D.
hasNotableFictionalBearer
Indicates that an entity is associated with at least one well-known fictional character that bears its name or designation.
-
E.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe608e5b08190a6d551793e8ed94b |
completed | March 31, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:15 p.m.