Triple
T26218440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lana Turner |
E655697
|
entity |
| Predicate | hadHusbandOrder |
P4764
|
FINISHED |
| Object |
third husband Fred May
Fred May was the third husband of Hollywood actress Lana Turner, known primarily for his brief marriage to the famed film star.
|
E1715318
|
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: third husband Fred May | Statement: [Lana Turner, hadHusbandOrder, third husband Fred May]
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: third husband Fred May Triple: [Lana Turner, hadHusbandOrder, third husband Fred May]
Generated description
Fred May was the third husband of Hollywood actress Lana Turner, known primarily for his brief marriage to the famed film star.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadHusbandOrder Context triple: [Lana Turner, hadHusbandOrder, third husband Fred May]
-
A.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
takenFromHusbandBy
Indicates that something previously belonging to a husband was removed or seized by another specified party.
-
C.
givenToSecondHusbandBy
Indicates that something was transferred or bestowed upon a person by their second husband.
-
D.
hadPartner
Indicates that an entity was in a romantic or life-partner relationship with another entity at some point in time.
-
E.
hadPartnerType
Indicates that an entity was associated with another entity in a specific type or category of partnership.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d1cd19081909f7575479d6b91ca |
completed | May 2, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11858f71f48190977ae6823c00d573 |
completed | May 23, 2026, 10:46 a.m. |
| NEDg | Description generation | batch_6a11863d1c3881909b35d2859710d956 |
completed | May 23, 2026, 10:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11871f0f9c81908b836c8d759bf8dc |
completed | May 23, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 8:55 p.m.