Triple
T5603622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelson Mandela memorial service 2013 |
E147179
|
entity |
| Predicate | attendeeEstimate |
P3846
|
FINISHED |
| Object | tens of thousands of people |
—
|
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: tens of thousands of people | Statement: [Nelson Mandela memorial service 2013, attendeeEstimate, tens of thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendeeEstimate Context triple: [Nelson Mandela memorial service 2013, attendeeEstimate, tens of thousands of people]
-
A.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
B.
approximateAudienceSize
chosen
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
C.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
D.
eventParticipant
Indicates that an entity takes part in, is involved in, or participates in a particular event.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020dce10c8190bf456602eec211d4 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1890ec8190b9e6fa488792e4d4 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.