Triple
T7722177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Street |
E175037
|
entity |
| Predicate | maximumAttendanceYear |
P18122
|
FINISHED |
| Object | 1949 |
—
|
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: 1949 | Statement: [Love Street, maximumAttendanceYear, 1949]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAttendanceYear Context triple: [Love Street, maximumAttendanceYear, 1949]
-
A.
peakYear
chosen
Indicates the year in which something reached its highest or most significant level, performance, or prominence.
-
B.
membershipPeakYear
Indicates the year in which an entity’s membership count reached its highest level.
-
C.
averageAttendanceHigh
Indicates that the typical or mean attendance level for an event, venue, or activity is considered high relative to a defined standard or threshold.
-
D.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
E.
grandFinalAttendance
Indicates the number of people who attended the grand final event.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.