Triple
T28243604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lone Pine Mall |
E712099
|
entity |
| Predicate | previousNameInStory |
P65
|
FINISHED |
| Object | Twin Pines Mall |
—
|
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: Twin Pines Mall | Statement: [Lone Pine Mall, previousNameInStory, Twin Pines Mall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousNameInStory Context triple: [Lone Pine Mall, previousNameInStory, Twin Pines Mall]
-
A.
previousNameUsedUntil
Indicates that a particular name was used for an entity up to (but not necessarily including) a specified end date or time.
-
B.
previousNarrator
Indicates that one entity served as the narrator immediately before another entity in a sequence of narrations.
-
C.
previousNamePeriod
Indicates the time span during which an entity was known by a former name before changing to its current name.
-
D.
previousTitle
Indicates that one title held or used by an entity directly preceded another title in sequence or time.
-
E.
formerName
chosen
Indicates that an entity was previously known by a different name in the past.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: April 27, 2026, 11 p.m.