Triple
T13105110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Angeles |
E310823
|
entity |
| Predicate | hasPopulationCharacteristicInFiction |
P97696
|
FINISHED |
| Object | densely populated |
—
|
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: densely populated | Statement: [San Angeles, hasPopulationCharacteristicInFiction, densely populated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationCharacteristicInFiction Context triple: [San Angeles, hasPopulationCharacteristicInFiction, densely populated]
-
A.
fictionalPopulation
Indicates that a location or setting has an imagined or non-real population, as found in fictional works.
-
B.
fandomCharacteristic
Indicates that an entity possesses a particular trait, behavior, or quality specifically in the context of its fandom or fan community.
-
C.
hasFictionalInhabitants
chosen
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
D.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
E.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98154c9f48190aeca779d97151759 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d98041a3548190a05ddd83dbb660fa |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:05 p.m.