Triple
T13341604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinfadi Market |
E317839
|
entity |
| Predicate | significantPlaceType |
P109097
|
FINISHED |
| Object | wholesale food distribution hub |
—
|
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: wholesale food distribution hub | Statement: [Xinfadi Market, significantPlaceType, wholesale food distribution hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantPlaceType Context triple: [Xinfadi Market, significantPlaceType, wholesale food distribution hub]
-
A.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
-
B.
historicLocationType
Indicates the specific kind or category of a place based on its historical significance or role.
-
C.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
D.
monumentType
Indicates the specific kind or category of monument that an entity is classified as.
-
E.
significantBuilding
Indicates that a building holds notable importance, prominence, or special status within a particular context (e.g., historical, cultural, architectural, or functional).
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d0379d481909a50fff31b19fed1 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99073e4708190843bda3a1ae78f43 |
completed | April 11, 2026, 12:06 a.m. |
Created at: April 9, 2026, 9:31 p.m.