Triple
T27291687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Riepe Rhodes |
E688644
|
entity |
| Predicate | hasNamesakeVenue |
P99932
|
FINISHED |
| Object |
Rhodes Field
Rhodes Field is a soccer stadium at the University of Pennsylvania that serves as the home field for the Penn Quakers men's and women's soccer teams.
|
E152845
|
NE FINISHED |
How this triple was built (3 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: Rhodes Field | Statement: [James Riepe Rhodes, hasNamesakeVenue, Rhodes Field]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rhodes Field Triple: [James Riepe Rhodes, hasNamesakeVenue, Rhodes Field]
Generated description
Rhodes Field is a soccer stadium at the University of Pennsylvania that serves as the home field for the Penn Quakers men's and women's soccer teams.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeVenue Context triple: [James Riepe Rhodes, hasNamesakeVenue, Rhodes Field]
-
A.
hasVenueName
Indicates that an entity has a specific name used to identify the venue where an event or activity takes place.
-
B.
hasSignatureVenueNamedAfter
Indicates that an entity’s primary or most iconic venue bears the name of another specified entity.
-
C.
venueAlsoKnownAs
Indicates that a venue has an alternative name or alias by which it is also known.
-
D.
hasNamesakeFeature
chosen
Indicates that one entity has a feature (such as a place, object, or structure) that is named after another entity.
-
E.
hasSuccessorVenueName
Indicates that one venue is followed or replaced by another venue, whose name is given as the successor venue name.
- F. None of above.
Provenance (6 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12629e33e481908cd8ca7a38772943 |
completed | May 24, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_6a126e52b7f48190a124771807a8f944 |
completed | May 24, 2026, 3:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a126ecee1a08190b1a70b1f8514546f |
completed | May 24, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 27, 2026, 11:15 a.m.