Triple
T2484948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsinghua University |
E55902
|
entity |
| Predicate | nationallyRankedAs |
P30985
|
FINISHED |
| Object | one of the top universities in China |
—
|
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: one of the top universities in China | Statement: [Tsinghua University, nationallyRankedAs, one of the top universities in China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationallyRankedAs Context triple: [Tsinghua University, nationallyRankedAs, one of the top universities in China]
-
A.
nationalRank
chosen
Indicates the position or standing of an entity within a ranking system at the national level.
-
B.
rankedAs
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
-
C.
rankedAmong
Indicates that an entity holds a specific position or status within a defined group, list, or hierarchy of comparable entities.
-
D.
rankedHighInUS
Indicates that something has achieved a relatively high ranking or position within the United States according to a specific metric or evaluation.
-
E.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.